Canine Detection of the Volatilome: A Review of Implications for Pathogen and Disease Detection

Volatile organic compounds in preen oil and feathers - a review

For a long time birds were assumed to be anosmic or at best microsmatic, with olfaction a poorly understood and seldom investigated part of avian physiology. The full viability of avian olfaction was first discovered through its functions in navigation and foraging. Subsequently, researchers have investigated the role of olfaction in different social and non-social contexts, including reproduction, kin recognition, predator avoidance, navigation and foraging. In parallel to the recognition of the importance of olfaction for avian social behaviour, there have been advances in the techniques and methods available for the sampling and analysis of trace volatiles and odourants, leading to insights into the chemistry underlying chemical communication in birds. This review provides (i) an overview of the current state of knowledge regarding the volatile chemical composition of preen oil and feathers, its phylogenetic coverage, chemical signatures and their potential functions, and (ii) a discussion of current methods used for the isolation and detection of volatiles. Finally, lines for future research are proposed.

Next-generation methods for early disease detection in crops

Plant pathogens are commonly identified in the field by the typical disease symptoms that they can cause. The efficient early detection and identification of pathogens are essential procedures to adopt effective management practices that reduce or prevent their spread in order to mitigate the negative impacts of the disease. In this review, the traditional and innovative methods for early detection of the plant pathogens highlighting their major advantages and limitations are presented and discussed. Traditional techniques of diagnosis used for plant pathogen identification are focused typically on the DNA, RNA (when molecular methods), and proteins or peptides (when serological methods) of the pathogens. Serological methods based on mainly enzyme-linked immunosorbent assay (ELISA) are the most common method used for pathogen detection due to their high-throughput potential and low cost. This technique is not particularly reliable and sufficiently sensitive for many pathogens detection during the asymptomatic stage of infection. For non-cultivable pathogens in the laboratory, nucleic acid-based technology is the best choice for consistent pathogen detection or identification. Lateral flow systems are innovative tools that allow fast and accurate results even in field conditions, but they have sensitivity issues to be overcome. PCR assays performed on last-generation portable thermocyclers may provide rapid detection results in situ. The advent of portable instruments can speed pathogen detection, reduce commercial costs, and potentially revolutionize plant pathology. This review provides information on current methodologies and procedures for the effective detection of different plant pathogens. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Olfaction in the canine cognitive and emotional processes: From behavioral and neural viewpoints to measurement possibilities

Domestic dogs (Canis familiaris) have excellent olfactory processing capabilities that are utilized widely in human society e.g., working with customs, police, and army; their scent detection is also used in guarding, hunting, mold-sniffing, searching for missing people or animals, and facilitating the life of the disabled. Sniffing and searching for odors is a natural, species-typical behavior and essential for the dog's welfare. While taking advantage of this canine ability widely, we understand its foundations and implications quite poorly. We can improve animal welfare by better understanding their olfactory world. In this review, we outline the olfactory processing of dogs in the nervous system, summarize the current knowledge of scent detection and differentiation; the effect of odors on the dogs' cognitive and emotional processes and the dog-human bond; and consider the methodological advancements that could be developed further to aid in our understanding of the canine world of odors.

Canine detection of chronic wasting disease (CWD) in laboratory and field settings

Chronic wasting disease (CWD) is a fatal transmissible spongiform encephalopathy that affects both free-ranging and farmed cervid species, including mule deer, white-tailed deer, and elk (Odocoileus hemionus, Odocoileus virginianus, and Cervus canadensis). Due to the long incubation period and variability of clinical signs, CWD can expand and spread to new areas before they reach diagnostically detectable levels. Antemortem testing methods currently available can be difficult to obtain and to be applied to the large numbers required for adequate surveillance. However, key volatile biomarkers could be harnessed for non-invasive antemortem surveillance. Detection dogs are the most effective tool currently available for volatile detection; dogs can effectively complete wildlife surveys at rates surpassing that of humans. This study is the first to demonstrate that trained detection dogs can be used as an antemortem test for CWD. First, we trained three dogs to differentiate between CWD-positive and CWD-negative white-tailed deer faeces in a laboratory setting. Dogs spent significantly more time at the positive sample than the negative samples, suggesting that they differentiated between the positive and negative volatile signatures. We then trained the same dogs to search for CWD-positive faecal samples in a more naturalistic field setting. In the field, dogs found 8/11 CWD-positive samples and had an average false detection rate of 13%. These results suggest that dogs can be trained to differentiate CWD-positive faeces from CWD-negative faeces in both laboratory and field settings. Future studies will compare canine accuracy to other antemortem methods, as well as improved canine training methods.

COVID-19 scent dog research highlights and synthesis during the pandemic of December 2019-April 2023

CONTEXT

This review was undertaken to provide information concerning the advancement of research in the area of COVID-19 screening and testing during the worldwide pandemic from December 2019 through April 2023. In this review, we have examined the safety, effectiveness, and practicality of utilizing trained scent dogs in clinical and public situations for COVID-19 screening. Specifically, results of 29 trained scent dog screening peer-reviewed studies were compared with results of real-time reverse-transcription polymerase chain reaction (RT-PCR) and rapid antigen (RAG) COVID-19 testing methods.

OBJECTIVES

The review aims to systematically evaluate the strengths and weaknesses of utilizing trained scent dogs in COVID-19 screening.

METHODS

At the time of submission of our earlier review paper in August 2021, we found only four peer-reviewed COVID-19 scent dog papers: three clinical research studies and one preprint perspective paper. In March and April 2023, the first author conducted new literature searches of the MEDLINE/PubMed, Google Scholar, and Cochrane Library websites. Again, the keyword phrases utilized for the searches included "COVID detection dogs," "COVID scent dogs," and "COVID sniffer dogs." The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 Checklist was followed to ensure that our review adhered to evidence-based guidelines for reporting. Utilizing the results of the reviewed papers, we compiled statistics to intercompare and summarize basic information concerning the scent dogs and their training, the populations of the study participants, the types of sampling methods, the comparative tests utilized, and the effectiveness of the scent dog screening.

RESULTS

A total of 8,043 references were identified through our literature search. After removal of duplicates, there were 7,843 references that were screened. Of these, 100 were considered for full-text eligibility, 43 were included for qualitative synthesis, and 29 were utilized for quantitative analysis. The most relevant peer-reviewed COVID-19 scent dog references were identified and categorized. Utilizing all of the scent dog results provided for this review, we found that 92.3 % of the studies reached sensitivities exceeding 80 and 32.0 % of the studies exceeding specificities of 97 %. However, 84.0 % of the studies reported specificities above 90 %. Highlights demonstrating the effectiveness of the scent dogs include: (1) samples of breath, saliva, trachea-bronchial secretions and urine as well as face masks and articles of clothing can be utilized; (2) trained COVID-19 scent dogs can detect presymptomatic and asymptomatic patients; (3) scent dogs can detect new SARS-CoV-2 variants and Long COVID-19; and (4) scent dogs can differentiate SARS-CoV-2 infections from infections with other novel respiratory viruses.

CONCLUSIONS

The effectiveness of the trained scent dog method is comparable to or in some cases superior to the real-time RT-PCR test and the RAG test. Trained scent dogs can be effectively utilized to provide quick (seconds to minutes), nonintrusive, and accurate results in public settings and thus reduce the spread of the COVID-19 virus or other viruses. Finally, scent dog research as described in this paper can serve to increase the medical community's and public's knowledge and acceptance of medical scent dogs as major contributors to global efforts to fight diseases.

The Olfaction Ability of Medical Detection Canine to Detect Prostate Cancer From Urine Samples: Progress Captured in Systematic Review and Meta-Analysis

Background

To date, early cancer detection is considered vital to reduce the global cancer burden through low-cost, but accurate screening modalities. The anatomical positioning of prostate cancer (PCa) created a potentially distinctive diagnostic method through the identification of volatile organic compounds (VOCs) in urine, which might be detectable not by humans but by canine species. This review aimed to capture the potential of the medical detection canine (MDC) to detect PCa by providing its diagnostic accuracy estimation on urine odor testing.

Methods

Databases, e.g., MEDLINE, Cochrane, ScienceDirect, and ProQuest, were searched to identify the studies. We focused on accessible original research, comparing the diagnostic utility of trained female MDC and histopathology examination as the gold standard for PCa diagnosis. The statistical analysis was performed in Meta-DiSc 1.4 and presented in diagnostic values, i.e., sensitivity (Sn), specificity (Sp), positive or negative likelihood ratio (LR+ or LR-), diagnostic odd ratio (DOR), and area under the curve (AUC) value, to conclude the Sn-Sp in a single outcome.

Results

Female German Shepherds were the most commonly utilized MDC from the five studies included in the final analysis. We estimate the pooled diagnostic value of eight different MDCs, with the findings as follows: Sn (0.95 (0.94 - 0.97)), Sp (0.92 (0.90 - 0.93)), LR+ (4.48 (1.90 - 10.58)), LR- (0.12 (0.01 - 1.42)), DOR (35.39 (2.90 - 432.53)), and an AUC value of 0.9232.

Conclusions

MDC's olfaction ability holds considerable potential on its diagnostic accuracies to distinguish the urine of PCa individuals by identifying its volatilome property.

Early Detection of Prostate Cancer: The Role of Scent

Prostate cancer (PCa) represents the cause of the second highest number of cancer-related deaths worldwide, and its clinical presentation can range from slow-growing to rapidly spreading metastatic disease. As the characteristics of most cases of PCa remains incompletely understood, it is crucial to identify new biomarkers that can aid in early detection. Despite the prostate-specific antigen serum (PSA) levels, prostate biopsy, and imaging representing the actual gold-standard for diagnosing PCa, analyzing volatile organic compounds (VOCs) has emerged as a promising new frontier. We and other authors have reported that highly trained dogs can recognize specific VOCs associated with PCa with high accuracy. However, using dogs in clinical practice has several limitations. To exploit the potential of VOCs, an electronic nose (eNose) that mimics the dog olfactory system and can potentially be used in clinical practice was designed. To explore the eNose as an alternative to dogs in diagnosing PCa, we conducted a systematic literature review and meta-analysis of available studies. PRISMA guidelines were used for the identification, screening, eligibility, and selection process. We included six studies that employed trained dogs and found that the pooled diagnostic sensitivity was 0.87 (95% CI 0.86–0.89; I2, 98.6%), the diagnostic specificity was 0.83 (95% CI 0.80–0.85; I2, 98.1%), and the area under the summary receiver operating characteristic curve (sROC) was 0.64 (standard error, 0.25). We also analyzed five studies that used an eNose to diagnose PCa and found that the pooled diagnostic sensitivity was 0.84 (95% CI, 0.80–0.88; I2, 57.1%), the diagnostic specificity was 0.88 (95% CI, 0.84–0.91; I2, 66%), and the area under the sROC was 0.93 (standard error, 0.03). These pooled results suggest that while highly trained dogs have the potentiality to diagnose PCa, the ability is primarily related to olfactory physiology and training methodology. The adoption of advanced analytical techniques, such as eNose, poses a significant challenge in the field of clinical practice due to their growing effectiveness. Nevertheless, the presence of limitations and the requirement for meticulous study design continue to present challenges when employing eNoses for the diagnosis of PCa.

Electronic Nose Development and Preliminary Human Breath Testing for Rapid, Non-Invasive COVID-19 Detection

We adapted an existing, spaceflight-proven, robust "electronic nose" (E-Nose) that uses an array of electrical resistivity-based nanosensors mimicking aspects of mammalian olfaction to conduct on-site, rapid screening for COVID-19 infection by measuring the pattern of sensor responses to volatile organic compounds (VOCs) in exhaled human breath. We built and tested multiple copies of a hand-held prototype E-Nose sensor system, composed of 64 chemically sensitive nanomaterial sensing elements tailored to COVID-19 VOC detection; data acquisition electronics; a smart tablet with software (App) for sensor control, data acquisition and display; and a sampling fixture to capture exhaled breath samples and deliver them to the sensor array inside the E-Nose. The sensing elements detect the combination of VOCs typical in breath at parts-per-billion (ppb) levels, with repeatability of 0.02% and reproducibility of 1.2%; the measurement electronics in the E-Nose provide measurement accuracy and signal-to-noise ratios comparable to benchtop instrumentation. Preliminary clinical testing at Stanford Medicine with 63 participants, their COVID-19-positive or COVID-19-negative status determined by concomitant RT-PCR, discriminated between these two categories of human breath with a 79% correct identification rate using "leave-one-out" training-and-analysis methods. Analyzing the E-Nose response in conjunction with body temperature and other non-invasive symptom screening using advanced machine learning methods, with a much larger database of responses from a wider swath of the population, is expected to provide more accurate on-the-spot answers. Additional clinical testing, design refinement, and a mass manufacturing approach are the main steps toward deploying this technology to rapidly screen for active infection in clinics and hospitals, public and commercial venues, or at home.

Sniffer dogs performance is stable over time in detecting COVID-19 positive samples and agrees with the rapid antigen test in the field

Rapid antigen diagnostic (RAD) tests have been developed for the identification of the SARS-CoV-2 infection. However, they require nasopharyngeal or nasal swab, which is invasive, uncomfortable, and aerosolising. The use of saliva test was also proposed but has not yet been validated. Trained dogs may efficiently smell the presence of SARS-CoV-2 in biological samples of infected people, but further validation is needed both in laboratory and in field. The present study aimed to (1) assess and validate the stability over a specific time period of COVID-19 detection in humans' armpit sweat by trained dogs thanks to a double-blind laboratory test-retest design, and (2) assess this ability when sniffing people directly. Dogs were not trained to discriminate against other infections. For all dogs (n. 3), the laboratory test on 360 samples yielded 93% sensitivity and 99% specificity, an 88% agreement with the Rt-PCR, and a moderate to strong test-retest correlation. When sniffing people directly (n. 97), dogs' (n. 5) overall sensitivity (89%) and specificity (95%) were significantly above chance level. An almost perfect agreement with RAD results was found (kappa 0.83, SE 0.05, p = 0.001). Therefore, sniffer dogs met appropriate criteria (e.g., repeatability) and WHO's target product profiles for COVID-19 diagnostics and produced very promising results in laboratory and field settings, respectively. These findings support the idea that biodetection dogs could help reduce the spread of the virus in high-risk environments, including airports, schools, and public transport.

Interactions between Humans and Dogs during the COVID-19 Pandemic: Recent Updates and Future Perspectives

COVID-19 is one of the deadliest epidemics. This pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but the role of dogs in spreading the disease in human society is poorly understood. This review sheds light on the limited susceptibility of dogs to COVID-19 infections which is likely attributed to the relatively low levels of angiotensin-converting enzyme 2 (ACE2) in the respiratory tract and the phylogenetic distance of ACE2 in dogs from the human ACE2 receptor. The low levels of ACE2 affect the binding affinity between spike and ACE2 proteins resulting in it being uncommon for dogs to spread the disease. To demonstrate the role of dogs in spreading COVID-19, we reviewed the epidemiological studies and prevalence of SARS-CoV-2 in dogs. Additionally, we discussed the use of detection dogs as a rapid and reliable method for effectively discriminating between SARS-CoV-2 infected and non-infected individuals using different types of samples (secretions, saliva, and sweat). We considered the available information on COVID-19 in the human-dog interfaces involving the possibility of transmission of COVID-19 to dogs by infected individuals and vice versa, the human-dog behavior changes, and the importance of preventive measures because the risk of transmission by domestic dogs remains a concern.

Is diagnostic performance of SARS-CoV-2 detection dogs reduced -due to virus variation- over the time?

Medical detection dogs have a high potential for use as alternative diagnostic tools not only for organic diseases, but also for infectious diseases. However, new variants emerging over time may affect the accuracy and sensitivity of diagnostic methods including medical detection dogs in case of viral pandemics. To the best of our knowledge, this is a pioneer study aimed to investigate diagnostic performances and generalization ability of SARS-CoV-2 detection dogs against the new variant after being trained with the original virus. Two SARS-CoV-2 detection dogs were used in this study. In total, 1002 samples including the Omicron variant were introduced to the dogs using a double-blinded design. Two different refresher training sessions were conducted to train the dogs to identify the scent of the Omicron variant. In the first refreshment training, mixed samples (original virus and Omicron variant) were used. The diagnostic performances of the dogs were significantly increased only after the second refreshment training where only the Omicron variant was introduced. This study illustrates that diagnostic performances of SARS-CoV-2 detection dogs were not consistent over time with the emerging new variants. Thus, refreshment training with new variant(s) should be conducted with every new variant which may affect the diagnostic performances of those dogs in such infectious outbreaks.

Remote Medical Scent Detection of Cancer and Infectious Diseases With Dogs and Rats: A Systematic Review

BACKGROUND

Remote medical scent detection of cancer and infectious diseases with dogs and rats has been an increasing field of research these last 20 years. If validated, the possibility of implementing such a technique in the clinic raises many hopes. This systematic review was performed to determine the evidence and performance of such methods and assess their potential relevance in the clinic.

METHODS

Pubmed and Web of Science databases were independently searched based on PRISMA standards between 01/01/2000 and 01/05/2021. We included studies aiming at detecting cancers and infectious diseases affecting humans with dogs or rats. We excluded studies using other animals, studies aiming to detect agricultural diseases, diseases affecting animals, and others such as diabetes and neurodegenerative diseases. Only original articles were included. Data about patients' selection, samples, animal characteristics, animal training, testing configurations, and performances were recorded.

RESULTS

A total of 62 studies were included. Sensitivity and specificity varied a lot among studies: While some publications report low sensitivities of 0.17 and specificities around 0.29, others achieve rates of 1 sensitivity and specificity. Only 6 studies were evaluated in a double-blind screening-like situation. In general, the risk of performance bias was high in most evaluated studies, and the quality of the evidence found was low.

CONCLUSIONS

Medical detection using animals' sense of smell lacks evidence and performances so far to be applied in the clinic. What odors the animals detect is not well understood. Further research should be conducted, focusing on patient selection, samples (choice of materials, standardization), and testing conditions. Interpolations of such results to free running detection (direct contact with humans) should be taken with extreme caution. Considering this synthesis, we discuss the challenges and highlight the excellent odor detection threshold exhibited by animals which represents a potential opportunity to develop an accessible and non-invasive method for disease detection.

Use of trained scent dogs for detection of COVID-19 and evidence of cost-saving

Background

One of the lessons learned from the coronavirus disease 2019 (COVID-19) pandemic is the importance of early, flexible, and rapidly deployable disease detection methods. Currently, diagnosis of COVID-19 requires the collection of oro/nasopharyngal swabs, nasal turbinate, anterior nares and saliva but as the pandemic continues, disease detection methods that can identify infected individuals earlier and more quickly will be crucial for slowing the spread of the virus. Previous studies have indicated that dogs can be trained to identify volatile organic compounds (VOCs) produced during respiratory infections. We sought to determine whether this approach could be applied for detection of COVID-19 in Rwanda and measured its cost-saving.

Methods

Over a period of 5 months, four dogs were trained to detect VOCs in sweat samples collected from human subjects confirmed positive or negative for COVID-19 by reverse transcription polymerase chain reaction (RT-PCR) testing. Dogs were trained using a detection dog training system (DDTS) and in vivo diagnosis. Samples were collected from 5,253 participants using a cotton pad swiped in the underarm to collect sweat samples. Statistical analysis was conducted using R statistical software.

Findings

From August to September 2021 during the Delta wave, the sensitivity of the dogs' COVID-19 detection ranged from 75.0 to 89.9% for the lowest- and highest-performing dogs, respectively. Specificity ranged from 96.1 to 98.4%, respectively. In the second phase coinciding with the Omicron wave (January-March 2022), the sensitivity decreased substantially from 36.6 to 41.5%, while specificity remained above 95% for all four dogs. The sensitivity and specificity by any positive sample detected by at least one dog was 83.9, 95% CI: 75.8-90.2 and 94.9%; 95% CI: 93.9-95.8, respectively. The use of scent detection dogs was also found to be cost-saving compared to antigen rapid diagnostic tests, based on a marginal cost of approximately $14,000 USD for testing of the 5,253 samples which makes 2.67 USD per sample. Testing turnaround time was also faster with the scent detection dogs, at 3 h compared to 11 h with routine diagnostic testing.

Conclusion

The findings from this study indicate that trained dogs can accurately identify respiratory secretion samples from asymptomatic and symptomatic COVID-19 patients timely and cost-effectively. Our findings recommend further uptake of this approach for COVID-19 detection.

The Use of Biological Sensors and Instrumental Analysis to Discriminate COVID-19 Odor Signatures

The spread of SARS-CoV-2, which causes the disease COVID-19, is difficult to control as some positive individuals, capable of transmitting the disease, can be asymptomatic. Thus, it remains critical to generate noninvasive, inexpensive COVID-19 screening systems. Two such methods include detection canines and analytical instrumentation, both of which detect volatile organic compounds associated with SARS-CoV-2. In this study, the performance of trained detection dogs is compared to a noninvasive headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) approach to identifying COVID-19 positive individuals. Five dogs were trained to detect the odor signature associated with COVID-19. They varied in performance, with the two highest-performing dogs averaging 88% sensitivity and 95% specificity over five double-blind tests. The three lowest-performing dogs averaged 46% sensitivity and 87% specificity. The optimized linear discriminant analysis (LDA) model, developed using HS-SPME-GC-MS, displayed a 100% true positive rate and a 100% true negative rate using leave-one-out cross-validation. However, the non-optimized LDA model displayed difficulty in categorizing animal hair-contaminated samples, while animal hair did not impact the dogs' performance. In conclusion, the HS-SPME-GC-MS approach for noninvasive COVID-19 detection more accurately discriminated between COVID-19 positive and COVID-19 negative samples; however, dogs performed better than the computational model when non-ideal samples were presented.

In search of COVID-19: The ability of biodetection canines to detect COVID-19 odours from clinical samples

BACKGROUND

COVID-19 continues to be a public health concern and the demand for fast and reliable screening tests remains. SARS-CoV-2 infection in humans generates a specific volatile organic compound signature; this 'volatilome' could be used to deploy highly trained canine scent detection teams if they could reliably detect odours from infected individuals.

METHODS

Two dogs were trained over 19 weeks to discriminate between the odours produced by breath, sweat, and gargle specimens collected from SARS-CoV-2 infected and uninfected individuals. Third party validation was conducted in a randomized double-blinded controlled manner using fresh odours obtained from different patients within 10 days of their first positive SARS-CoV-2 molecular result.

RESULTS

Cumulatively, the dogs completed 299 training sessions on odours from 108 unique participants. Validation was conducted over 2 days with 120 new odours. Twenty-four were odours collected from SARS-CoV-2 positive individuals (8 gargle, 8 sweat, and 8 breath); 21 were from SARS-CoV-2 negative individuals (5 gargle, 8 sweat, and 8 breath) and the remaining 75 were odours that the dogs could have associated with the target odour during training. The dogs were able to identify odours from positive specimens with an overall sensitivity of 100% and a specificity of 87.5%. Considering a community prevalence of 10%, the combined negative predictive value of the dogs was 100% and the positive predictive value was 47.1%.

CONCLUSIONS

Multiple dogs can be trained to accurately detect SARS-CoV-2 positive individuals. Future research is required to determine how and when canine scent detection teams should be deployed.

Marker Substances in the Aroma of Truffles

The aim of this study was to identify specific truffle marker substances within the truffle aroma. The aroma profile of different truffle species was analyzed using static headspace sampling with gas chromatography mass spectrometry analysis (SHS/GC-MS). Possible marker substances were identified, taking the additional literature into account. The selected marker substances were tested in an experiment with 19 truffle dogs. The hypothesis “If trained truffle dogs recognize the substances as supposed truffles in the context of an experiment, they can be regarded as specific” was made. As it would be nearly impossible to investigate every other possible emitter of the same compounds to determine their specificity, this hypothesis was a reasonable approximation. We were interested in the question of what it is the dogs actually search for on a chemical level and whether we can link their ability to find truffles to one or more specific marker substances. The results of the dog experiment are not as unambiguous as could have been expected based on the SHS/GC-MS measurements. Presumably, the truffle aroma is mainly characterized and perceived by dogs by dimethyl sulfide and dimethyl disulfide. However, as dogs are living beings and not analytical instruments, it seems unavoidable that one must live with some degree of uncertainty regarding these results.

Canine discrimination of ovarian cancer through volatile organic compounds

Ovarian cancer has a high mortality rate due to its unclear symptomology and the lack of precise early detection tools. If detected in the first stage, over 90% of patients reach remission. As such, developing a reliable method of early detection is crucial in reducing the mortality rate of the disease. One potential method would be to identify specific biomarkers that are unique to ovarian cancer, which could be detected using a blood test. While this can be done using gas chromatography - mass spectrometry (GC-MS), identifying these biomarkers is an enormous task. One way to expedite the process is to utilize trained scent detection canines. In this study, dogs who were previously trained to respond to positive blood samples from ovarian cancer patients were then tested on their ability to recognize samples prepared by micro-preparative gas chromatography (MP-GC) techniques. MP-GC employed a gradient-cooled glass tube connected to the GC outlet to collect GC eluents containing the plasma-derived volatiles in positive blood samples. These post-column fractions were collected at the exit of the GC according to their eluent times (i.e., 0-15 min, 15-25 min and 25-35 min or 0-35 min) and these full or fractional collections were presented to the trained dogs to judge their responses. Dogs' time spent investigating the odor was used as an indication of odor recognition and was significantly longer on the early (0-15 min) and middle (15-25 min) fractions of the ovarian cancer than the late (25-35 min) fraction of plasma odorants or either the negative fractions or distractors odorants. These findings suggest that characteristic odor biomarkers of ovarian cancer for dogs may exist in the relatively small and more volatile compounds. Additionally, variation between dogs suggests that there may be a number of different biomarkers that can be used to identify ovarian cancer.

Exhaled VOCs can discriminate subjects with COVID-19 from healthy controls

COVID-19 detection currently relies on testing by reverse transcription polymerase chain reaction (RT-PCR) or antigen testing. However, SARS-CoV-2 is expected to cause significant metabolic changes in infected subjects due to both metabolic requirements for rapid viral replication and host immune responses. Analysis of volatile organic compounds (VOCs) from human breath can detect these metabolic changes and is therefore an alternative to RT-PCR or antigen assays. To identify VOC biomarkers of COVID-19, exhaled breath samples were collected from two sample groups into Tedlar bags: negative COVID-19 (n= 12) and positive COVID-19 symptomatic (n= 14). Next, VOCs were analyzed by headspace solid phase microextraction coupled to gas chromatography-mass spectrometry. Subjects with COVID-19 displayed a larger number of VOCs as well as overall higher total concentration of VOCs (p< 0.05). Univariate analyses of qualified endogenous VOCs showed approximately 18% of the VOCs were significantly differentially expressed between the two classes (p< 0.05), with most VOCs upregulated. Machine learning multivariate classification algorithms distinguished COVID-19 subjects with over 95% accuracy. The COVID-19 positive subjects could be differentiated into two distinct subgroups by machine learning classification, but these did not correspond with significant differences in number of symptoms. Next, samples were collected from subjects who had previously donated breath bags while experiencing COVID-19, and subsequently recovered (COVID Recovered subjects (n= 11)). Univariate and multivariate results showed >90% accuracy at identifying these new samples as Control (COVID-19 negative), thereby validating the classification model and demonstrating VOCs dysregulated by COVID are restored to baseline levels upon recovery.

A Novel Method for Training the Interdiction of Restricted and Hazardous Biological Materials by Detection Dogs

The interdiction of restricted and hazardous biological agents presents challenges for any detection method due to the inherent complexity of sample type and accessibility. Detection capabilities for this category of agents are limited and restricted in their mobility, adaptability and efficiency. The potential for identifying biological agents through a volatile organic compound (VOC) signature presents an opportunity to use detection dogs in a real-time mobile capacity for surveillance and screening strategies. However, the safe handling and access to the materials needed for training detection dogs on restricted or hazardous biological agents prevents its broader application in this field. This study evaluated the use of a polymer-based training aid in a viral detection model using bovine viral diarrhea virus mimicking biosafety level 3+ agent conditions. After the biological agent-based odor was absorbed into the polymer, the aid was rendered safe for handling through a rigorous sterilization process. The viral culture-based training aid was then used to train a cohort of detection dogs (n = 6) to discriminate agent-based target odor in culture from relevant distractor odors including non-target biological agent-based odors. Following culture-based training, dogs were tested for generalization to aids with infected animal sample-based odors across five sample types (fecal, blood, nasal, saliva, and urine). Within the context of the polymer-based training aid system, dogs were successfully trained to detect and discriminate a representative biological viral agent-based odor from distractor odors with a 97.22% (±2.78) sensitivity and 97.11% (±1.94) specificity. Generalization from the agent-based odor to sample-based odors ranged from 65.40% (±8.98) to 91.90 % (±6.15) sensitivity and 88.61% (±1.46) to 96.00% (±0.89) specificity across the sample types. The restrictive nature for mimicking the access and handling of a BSL 3+ agent presented challenges that required a strict study design uncommon to standard detection dog training and odor presentation. This study demonstrates the need to further evaluate the utility and challenges of training detection dogs to alert to biological samples using safe and manageable training aids.

Scent dogs in detection of COVID-19: triple-blinded randomised trial and operational real-life screening in airport setting

Objective

To estimate scent dogs’ diagnostic accuracy in identification of people infected with SARS-CoV-2 in comparison with reverse transcriptase polymerase chain reaction (RT-PCR). We conducted a randomised triple-blinded validation trial, and a real-life study at the Helsinki-Vantaa International Airport, Finland.

Methods

Four dogs were trained to detect COVID-19 using skin swabs from individuals tested for SARS-CoV-2 by RT-PCR. Our controlled triple-blinded validation study comprised four identical sets of 420 parallel samples (from 114 individuals tested positive and 306 negative by RT-PCR), randomly presented to each dog over seven trial sessions. In a real-life setting the dogs screened skin swabs from 303 incoming passengers all concomitantly examined by nasal swab SARS-CoV-2 RT-PCR. Our main outcomes were variables of diagnostic accuracy (sensitivity, specificity, positive predictive value, negative predictive value) for scent dog identification in comparison with RT-PCR.

Results

Our validation experiments had an overall accuracy of 92% (95% CI 90% to 93%), a sensitivity of 92% (95% CI 89% to 94%) and a specificity of 91% (95% CI 89% to 93%) compared with RT-PCR. For our dogs, trained using the wild-type virus, performance was less accurate for the alpha variant (89% for confirmed wild-type vs 36% for alpha variant, OR 14.0, 95% CI 4.5 to 43.4). In the real-life setting, scent detection and RT-PCR matched 98.7% of the negative swabs. Scant airport prevalence (0.47%) did not allow sensitivity testing; our only SARS-CoV-2 positive swab was not identified (alpha variant). However, ad hoc analysis including predefined positive spike samples showed a total accuracy of 98% (95% CI 97% to 99%).

Conclusions

This large randomised controlled triple-blinded validation study with a precalculated sample size conducted at an international airport showed that trained scent dogs screen airport passenger samples with high accuracy. One of our findings highlights the importance of continuous retraining as new variants emerge. Using scent dogs may present a valuable approach for high-throughput, rapid screening of large numbers of people.

Dogs Detecting COVID-19 From Sweat and Saliva of Positive People: A Field Experience in Mexico

Context

Molecular tests are useful in detecting COVID-19, but they are expensive in developing countries. COVID-19-sniffing dogs are an alternative due to their reported sensitivity (&gt;80%) and specificity (&gt;90%). However, most of the published evidence is experimental, and there is a need to determine the performance of the dogs in field conditions. Hence, we aimed to test the sensitivity and specificity of COVID-19-sniffing dogs in the field.

Methods

We trained four dogs with sweat and three dogs with saliva of COVID-19-positive patients, respectively, for 4.5 months. The samples were obtained from a health center in Hermosillo, Sonora, with the restriction to spend 5 min per patient. We calculated sensitivity, specificity, and their 95% confidence intervals (CI).

Results

Two sweat-sniffing dogs reached 76 and 80% sensitivity, with the 95% CI not overlapping the random value of 50%, and 75 and 88% specificity, with the 95% CI not overlapping the 50% value. The 95% CI of the sensitivity and specificity of the other two sweat dogs overlapped the 50% value. Two saliva-sniffing dogs had 70 and 78% sensitivity, and the 95% CI of their sensitivity and specificity did not overlap the 50% value. The 95% CI of the third dog's sensitivity and specificity overlapped the 50% value.

Conclusion

Four of the six dogs were able to detect positive samples of patients with COVID-19, with sensitivity and specificity values significantly different from random in the field. We considered the performance of the dogs promising because it is reasonable to expect that with gauze exposed for a longer time to sweat and saliva of people with COVID-19, their detection capacity would improve. The target is to reach the sensitivity range requested by the World Health Organization for the performance of an antigen test (≥80% sensitivity, ≥97% specificity). If so, dogs could become important allies for the control of the COVID-19 pandemic, especially in developing countries.

Preliminary method for profiling volatile organic compounds in breath that correlate with pulmonary function and other clinical traits of subjects diagnosed with cystic fibrosis: a pilot study

Cystic fibrosis (CF) is characterized by chronic respiratory infections which progressively decrease lung function over time. Affected individuals experience episodes of intensified respiratory symptoms called pulmonary exacerbations (PEx) which accelerate pulmonary function decline and decrease survival. There is no standard classification for PEx, which results in treatments that are heterogeneous. Improving PEx classification and management is a significant priority for people with CF. Previous studies have shown volatile organic compounds (VOCs) in exhaled breath can be used as biomarkers because they are products of metabolic pathways dysregulated by different diseases. To provide insights on PEx classification and other clinical factors, exhaled breath was collected from subjects with CF, with some experiencing PEx and others at baseline. Exhaled breath was collected in Tedlar bags during tidal breathing for VOC analysis by solid phase microextraction coupled to gas chromatography-mass spectrometry. Statistical significance testing between quantitative and categorical clinical variables displayed percent-predicted forced expiratory volume in one second (FEV1pp) was decreased in subjects experiencing PEx. VOCs correlating with other clinical variables (body mass index, age, use of highly effective modulator therapies, and need for antibiotics) were also explored. VOCs correlating to potential confounding variables were removed and analyzed by regression for correlations with FEV1pp measurements. The VOC with the highest correlation with FEV1pp (3,7-dimethyldecane) also gave the lowest p-value when comparing subjects at baseline and during PEx. Receiver operator characteristic curves showed 3,7-dimethyldecane had a higher ability to classify PEx (area under the curve (AUC) = 0.91) relative to FEV1pp values at collection (AUC = 0.83). However, normalized ΔFEV1pp values had the highest capability to distinguish PEx (AUC = 0.93). These results show that exhaled VOCs may be a source of biomarkers for various clinical traits of CF, including PEx, that should be explored in larger sample cohorts and validation studies.

LABRADOR-A Computational Workflow for Virus Detection in High-Throughput Sequencing Data

High-throughput sequencing (HTS) allows detection of known and unknown viruses in samples of broad origin. This makes HTS a perfect technology to determine whether or not the biological products, such as vaccines are free from the adventitious agents, which could support or replace extensive testing using various in vitro and in vivo assays. Due to bioinformatics complexities, there is a need for standardized and reliable methods to manage HTS generated data in this field. Thus, we developed LABRADOR—an analysis pipeline for adventitious virus detection. The pipeline consists of several third-party programs and is divided into two major parts: (i) direct reads classification based on the comparison of characteristic profiles between reads and sequences deposited in the database supported with alignment of to the best matching reference sequence and (ii) de novo assembly of contigs and their classification on nucleotide and amino acid levels. To meet the requirements published in guidelines for biologicals’ safety we generated a custom nucleotide database with viral sequences. We tested our pipeline on publicly available HTS datasets and showed that LABRADOR can reliably detect viruses in mixtures of model viruses, vaccines and clinical samples.

Routine Decontamination of Working Canines: A Study on the Removal of Superficial Gross Contamination

Odor detection canines are a valuable resource used by multiple agencies for the sensitive detection of explosives, narcotics, firearms, agricultural products, and even human bodies. These canines and their handlers are frequently deployed to pathogen-contaminated environments or to work in close proximity with potentially sick individuals. Appropriate decontamination protocols must be established to mitigate both canine and handler exposure in these scenarios. Despite this potential risk, extremely limited guidance is available on routine canine decontamination from pathogenic biological materials. In this article, we evaluate the ability of several commercial off-the-shelf cleansing products, used in wipe form, to remove superficial contamination from fur, canine equipment, and toys. Using Glo Germ MIST as a proxy for biological contamination, our analysis demonstrated more than a 90% average reduction in contamination after wiping with a Nolvasan scrub solution, 0.5% chlorhexidine solution, or 70% isopropyl alcohol. Wiping with nondisinfectant baby wipes or water yielded an almost 80% average removal of contaminant from all surfaces. Additionally, researchers used Gwet's AC2 measurement to assess interrater reliability, which demonstrated substantial agreement (P < .001). These data provide key insights toward the development of a rapid, convenient, and fieldable alternative to traditional water-intensive bathing of working canines.

Canine Olfactory Detection of SARS-COV2-Infected Patients: A One Health Approach

The aim of the present study is to apply the canine olfactory sensitivity to detect COVID-19-positive axillary sweat samples as a One Health approach in Latin America. One hundred volunteers with COVID-like symptoms were invited to participate, and both axillary sweat samples for dog detection and nasopharynx/oropharynx swabs for qPCR were collected. Two dogs, previously trained, detected 97.4% of the samples positive for COVID-19, including a false-negative qPCR-test, and the positive predictive value was 100% and the negative predictive value was 98.2%. Therefore, we can conclude that canine olfactory sensitivity can detect a person infected with COVID-19 through axillary sweat successfully and could be used as an alternative to screen them without invasive testing.

Highly sensitive scent-detection of COVID-19 patients in vivo by trained dogs

Timely and accurate diagnostics are essential to fight the COVID-19 pandemic, but no test satisfies both conditions. Dogs can scent-identify the unique odors of volatile organic compounds generated during infection by interrogating specimens or, ideally, the body of a patient. After training 6 dogs to detect SARS-CoV-2 by scent in human respiratory secretions (in vitro diagnosis), we retrained 5 of them to search and find the infection by scenting the patient directly (in vivo screening). Then, efficacy trials were designed to compare the diagnostic performance of the dogs against that of the rRT-PCR in 848 human subjects: 269 hospitalized patients (COVID-19 prevalence 30.1%), 259 hospital staff (prevalence 2.7%), and 320 government employees (prevalence 1.25%). The limit of detection in vitro was lower than 10-12 copies ssRNA/mL. During in vivo efficacy experiments, our 5 dogs detected 92 COVID-19 positive patients among the 848 study subjects. The alert (lying down) was immediate, with 95.2% accuracy and high sensitivity (95.9%; 95% C.I. 93.6-97.4), specificity (95.1%; 94.4-95.8), positive predictive value (69.7%; 65.9-73.2), and negative predictive value (99.5%; 99.2-99.7) in relation to rRT-PCR. Seventy-five days after finishing in vivo efficacy experiments, a real-life study (in vivo effectiveness) was executed among the riders of the Metro System of Medellin, deploying the human-canine teams without previous training or announcement. Three dogs were used to examine the scent of 550 volunteers who agreed to participate, both in test with canines and in rRT-PCR testing. Negative predictive value remained at 99.0% (95% C.I. 98.3-99.4), but positive predictive value dropped to 28.2% (95% C.I. 21.1-36.7). Canine scent-detection in vivo is a highly accurate screening test for COVID-19, and it detects more than 99% of infected individuals independent of key variables, such as disease prevalence, time post-exposure, or presence of symptoms. Additional training is required to teach the dogs to ignore odoriferous contamination under real-life conditions.

Canine Olfaction: Physiology, Behavior, and Possibilities for Practical Applications

Simple Summary

Dogs have an extraordinary olfactory capability, which far exceeds that of humans. Dogs’ sense of smell seems to be the main sense, allowing them to not only gather both current and historical information about their surrounding environment, but also to find the source of the smell, which is crucial for locating food, danger, or partners for reproduction. Dogs can be trained by humans to use their olfactory abilities in a variety of fields, with a detection limit often much lower than that of sophisticated laboratory instruments. The specific anatomical and physiological features of dog olfaction allow humans to achieve outstanding results in the detection of drugs, explosives, and different illnesses, such as cancer, diabetes, or infectious disease. This article provides an overview of the anatomical features and physiological mechanisms involved in the process of odor detection and identification, as well as behavioral aspects of canine olfaction and its use in the service of humans in many fields.

Abstract

Olfaction in dogs is crucial for gathering important information about the environment, recognizing individuals, making decisions, and learning. It is far more specialized and sensitive than humans’ sense of smell. Using the strength of dogs’ sense of smell, humans work with dogs for the recognition of different odors, with a precision far exceeding the analytical capabilities of most modern instruments. Due to their extremely sensitive sense of smell, dogs could be used as modern, super-sensitive mobile area scanners, detecting specific chemical signals in real time in various environments outside the laboratory, and then tracking the odor of dynamic targets to their source, also in crowded places. Recent studies show that dogs can detect not only specific scents of drugs or explosives, but also changes in emotions as well as in human cell metabolism during various illnesses, including COVID-19 infection. Here, we provide an overview of canine olfaction, discussing aspects connected with anatomy, physiology, behavioral aspects of sniffing, and factors influencing the olfactory abilities of the domestic dog (Canis familiaris).

Canine olfactory detection and its relevance to medical detection

The extraordinary olfactory sense of canines combined with the possibility to learn by operant conditioning enables dogs for their use in medical detection in a wide range of applications. Research on the ability of medical detection dogs for the identification of individuals with infectious or non-infectious diseases has been promising, but compared to the well-established and-accepted use of sniffer dogs by the police, army and customs for substances such as money, explosives or drugs, the deployment of medical detection dogs is still in its infancy. There are several factors to be considered for standardisation prior to deployment of canine scent detection dogs. Individual odours in disease consist of different volatile organic molecules that differ in magnitude, volatility and concentration. Olfaction can be influenced by various parameters like genetics, environmental conditions, age, hydration, nutrition, microbiome, conditioning, training, management factors, diseases and pharmaceuticals. This review discusses current knowledge on the function and importance of canines' olfaction and evaluates its limitations and the potential role of the dog as a biomedical detector for infectious and non-infectious diseases.

The "olfactory fingerprint": can diagnostics be improved by combining canine and digital noses?

A sniffer (detecting) dog is conventionally defined as an animal trained to use its olfactory perceptions for detecting a vast array of substances, mostly volatile organic compounds (VOCs), including those exceptionally or exclusively generated in humans bearing specific pathologies. Such an extraordinary sniffing performance translates into the capability of detecting compounds close to the femtomolar level, with performance comparable to that of current mass spectrometry-based laboratory applications. Not only can dogs accurately detect "abnormal volatilomes" reflecting something wrong happening to their owners, but they can also perceive visual, vocal and behavioral signals, which altogether would contribute to raise their alertness. Although it seems reasonable to conclude that sniffer dogs could never be considered absolutely "diagnostic" for a given disorder, several lines of evidence attest that they may serve as efficient screening aids for many pathological conditions affecting their human companions. Favorable results have been obtained in trials on cancers, diabetes, seizures, narcolepsy and migraine, whilst interesting evidence is also emerging on the capability of early and accurately identifying patients with infectious diseases. This would lead the way to proposing an "olfactory fingerprint" loop, where evidence that dogs can identify the presence of human pathologies provides implicit proof of the existence of disease-specific volatilomes, which can be studied for developing laboratory techniques. Contextually, the evidence that specific pathologies are associated with abnormal VOC generation may serve as reliable basis for training dogs to detect these compounds, even (or especially) in patients at an asymptomatic phase.

Scent dog identification of SARS-CoV-2 infections in different body fluids

Background

The main strategy to contain the current SARS-CoV-2 pandemic remains to implement a comprehensive testing, tracing and quarantining strategy until vaccination of the population is adequate. Scent dogs could support current testing strategies.

Methods

Ten dogs were trained for 8 days to detect SARS-CoV-2 infections in beta-propiolactone inactivated saliva samples. The subsequent cognitive transfer performance for the recognition of non-inactivated samples were tested on three different body fluids (saliva, urine, and sweat) in a randomised, double-blind controlled study.

Results

Dogs were tested on a total of 5242 randomised sample presentations. Dogs detected non-inactivated saliva samples with a diagnostic sensitivity of 84% (95% CI: 62.5–94.44%) and specificity of 95% (95% CI: 93.4–96%). In a subsequent experiment to compare the scent recognition between the three non-inactivated body fluids, diagnostic sensitivity and specificity were 95% (95% CI: 66.67–100%) and 98% (95% CI: 94.87–100%) for urine, 91% (95% CI: 71.43–100%) and 94% (95% CI: 90.91–97.78%) for sweat, 82% (95% CI: 64.29–95.24%), and 96% (95% CI: 94.95–98.9%) for saliva respectively.

Conclusions

The scent cognitive transfer performance between inactivated and non-inactivated samples as well as between different sample materials indicates that global, specific SARS-CoV-2-associated volatile compounds are released across different body secretions, independently from the patient’s symptoms. All tested body fluids appear to be similarly suited for reliable detection of SARS-CoV-2 infected individuals.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06411-1.

COVID-19 sniffer dog experimental training: Which protocol and which implications for reliable sidentification?

The introduction of trained sniffer dogs for COVID‐19 detection could be an opportunity, as previously described for other diseases. Dogs could be trained to detect volatile organic compounds (VOCs), the whiff of COVID‐19. Dogs involved in the study were three, one male and two females from different breeds, Black German Shepherd, German Shepherd, and Dutch Shepherd. The training was performed using sweat samples from SARS‐CoV2 positive patients and from SARS‐Cov2 free patients admitted at the University Hospital Campus Bio‐medico of Rome. Gauze with sweat was collected in a glass jar with a metal top and put in metal boxes used for dog training. The dog training protocol was performed in two phases: the olfactory conditioning and the olfactory discrimination research. The training planning was focused on the switch moment for the sniffer dog, the moment when the dog was able to identify VOCs specific for COVID‐19. At this time, the dog was able to identify VOCs specific for COVID‐19 with significant reliability, in terms of the number of correct versus incorrect (p < 0.0001) reporting. In conclusion, this protocol could provide a useful tool for sniffer dogs' training and their introduction in a mass screening context. It could be cheaper and faster than a conventional testing method.

New method of screening for COVID-19 disease using sniffer dogs and scents from axillary sweat samples

BACKGROUND

Early screening for COVID-19 is needed to limit the spread of the virus. The aim of this study is to test if the sniffer dogs can be successfully trained to identify subjects with COVID-19 for 'proof of concept' and 'non-inferiority' against PCR. We are calling this method, Dognosis (DN).

METHODS

Four hundred and fifty-nine subjects were included, 256 (Group 'P') were known cases of COVID-19 (PCR positive, some with and some without symptoms) and 203 (Group 'C') were PCR negative and asymptomatic (control). Samples were obtained from the axillary sweat of each subject in a masked fashion. Two dogs trained to detect specific Volatile Organic Compounds for COVID-19 detection were used to test each sample.

RESULTS

[DN] turned out positive (+) in all the cases that were PCR positive (100% sensitivity). On the other hand, [DN] turned positive (+) in an average of 12.5 cases (6.2%) that were initially PCR negative (apparent specificity of 93.8%). When the PCR was repeated, true specificity was 97.2%. These parameters varied in subgroups from 100% sensitivity and 99% specificity in symptomatic patients to 100% sensitivity and 93% specificity in asymptomatic patients.

CONCLUSION

DN method shows high sensitivity and specificity in screening COVID-19 patients.

Preliminary accuracy of COVID-19 odor detection by canines and HS-SPME-GC-MS using exhaled breath samples

The novel coronavirus SARS-CoV-2, since its initial outbreak in Wuhan, China has led to a worldwide pandemic and has shut down nations. As with any outbreak, there is a general strategy of detection, containment, treatment and/or cure. The authors would argue that rapid and efficient detection is critical and required to successful management of a disease. The current study explores and successfully demonstrates the use of canines to detect COVID-19 disease in exhaled breath. The intended use was to detect the odor of COVID-19 on contaminated surfaces inferring recent deposition of infectious material from a COVID-19 positive individual. Using masks obtained from hospitalized patients that tested positive for COVID-19 disease, four canines were trained and evaluated for their ability to detect the disease. All four canines obtained an accuracy >90% and positive predictive values ranging from ~73 to 93% after just one month of training.

The detection dogs test is more sensitive than real-time PCR in screening for SARS-CoV-2

In January 2020, the coronavirus disease was declared, by the World Health Organization as a global public health emergency. Recommendations from the WHO COVID Emergency Committee continue to support strengthening COVID surveillance systems, including timely access to effective diagnostics. Questions were raised about the validity of considering the RT-PCR as the gold standard in COVID-19 diagnosis. It has been suggested that a variety of methods should be used to evaluate advocated tests. Dogs had been successfully trained and employed to detect diseases in humans. Here we show that upon training explosives detection dogs on sniffing COVID-19 odor in patients’ sweat, those dogs were able to successfully screen out 3249 individuals who tested negative for the SARS-CoV-2, from a cohort of 3290 individuals. Additionally, using Bayesian analysis, the sensitivity of the K9 test was found to be superior to the RT-PCR test performed on nasal swabs from a cohort of 3134 persons. Given its high sensitivity, short turn-around-time, low cost, less invasiveness, and ease of application, the detection dogs test lends itself as a better alternative to the RT-PCR in screening for SARS-CoV-2 in asymptomatic individuals.

Hag-Ali and colleagues highlight the potential for using trained dogs for detecting COVID-19 positive patients. The dogs, originally trained for explosives detection, were able to detect COVID-19 positive sweat samples with a sensitivity rivaling the gold-standard RT-PCR test currently used.

Operational Canine

Operational K9s encompass a unique population of working dogs that serve as a force multiplier in various civilian law enforcement, force protection, search and rescue, and humanitarian operations. These elite canines do not volunteer to serve, yet they are some of the most faithful and dependable operators in the field. They undoubtedly perform an invaluable service in today's society and are owed a tremendous debt of gratitude for their selfless service, loyalty, and sacrifices. This article describes the unique characteristics and occupational hazards that pertain to the community of Operational K9s.

Biodetection of a specific odor signature in mallard feces associated with infection by low pathogenic avian influenza A virus

Outbreaks of avian influenza virus (AIV) infection included the spread of highly pathogenic AIV in commercial poultry and backyard flocks in the spring of 2015. This resulted in estimated losses of more than $8.5 million from federal government expenditures, $1.6 billion from direct losses to produces arising from destroyed turkey and chicken egg production, and economy-wide indirect costs of $3.3 billion from impacts on retailers and the food service industries. Additionally, these outbreaks resulted in the death or depopulation of nearly 50 million domestic birds. Domesticated male ferrets (Mustela putorius furo) were trained to display a specific conditioned behavior (i.e. active scratch alert) in response to feces from AIV-infected mallards in comparison to feces from healthy ducks. In order to establish that ferrets were identifying samples based on odors associated with infection, additional experiments controlled for potentially confounding effects, such as: individual duck identity, housing and feed, inoculation concentration, and day of sample collection (post-infection). A final experiment revealed that trained ferrets could detect AIV infection status even in the presence of samples from mallards inoculated with Newcastle disease virus or infectious laryngotracheitis virus. These results indicate that mammalian biodetectors are capable of discriminating the specific odors emitted from the feces of non-infected versus AIV infected mallards, suggesting that the health status of waterfowl can be evaluated non-invasively for AIV infection via monitoring of volatile fecal metabolites. Furthermore, in situ monitoring using trained biodetectors may be an effective tool for assessing population health.

Multi-Odor Discrimination by Rat Sniffing for Potential Monitoring of Lung Cancer and Diabetes

The discrimination learning of multiple odors, in which multi-odor can be associated with different responses, is important for responding quickly and accurately to changes in the external environment. However, very few studies have been done on multi-odor discrimination by animal sniffing. Herein, we report a novel multi-odor discrimination system by detection rats based on the combination of 2-Choice and Go/No-Go (GNG) tasks into a single paradigm, in which the Go response of GNG was replaced by 2-Choice, for detection of toluene and acetone, which are odor indicators of lung cancer and diabetes, respectively. Three of six trained rats reached performance criterion, in 12 consecutive successful tests within a given set or over 12 sets with a success rate of over 90%. Through a total of 1300 tests, the trained animals (N = 3) showed multi-odor sensing performance with 88% accuracy, 87% sensitivity and 90% specificity. In addition, a dependence of behavior response time on odor concentrations under given concentration conditions was observed, suggesting that the system could be used for quantitative measurements. Furthermore, the animals’ multi-odor sensing performance has lasted for 45 days, indicating long-term stability of the learned multi-odor discrimination. These findings demonstrate that multi-odor discrimination can be achieved by rat sniffing, potentially providing insight into the rapid, accurate and cost-effective multi-odor monitoring in the lung cancer and diabetes.

Enhancing the Selection and Performance of Working Dogs

Dogs perform a variety of integral roles in our society, engaging in work ranging from assistance (e.g., service dogs, guide dogs) and therapy to detection (e.g., search-and-rescue dogs, explosive detection dogs) and protection (e.g., military and law enforcement dogs). However, success in these roles, which requires dogs to meet challenging behavioral criteria and to undergo extensive training, is far from guaranteed. Therefore, enhancing the selection process is critical for the effectiveness and efficiency of working dog programs and has the potential to optimize how resources are invested in these programs, increase the number of available working dogs, and improve working dog welfare. In this paper, we review two main approaches for achieving this goal: (1) developing selection tests and criteria that can efficiently and effectively identify ideal candidates from the overall pool of candidate dogs, and (2) developing approaches to enhance performance, both at the individual and population level, via improvements in rearing, training, and breeding. We summarize key findings from the empirical literature regarding best practices for assessing, selecting, and improving working dogs, and conclude with future steps and recommendations for working dog organizations, breeders, trainers, and researchers.

Dog Owners' Survey reveals Medical Alert Dogs can alert to multiple conditions and multiple people

Medical Alert Dogs (MADs) are a promising support system for a variety of medical conditions. Emerging anecdotal reports suggest that dogs may alert to additional health conditions and different people other than those that they were trained for or initially began alerting. As the use of medical alert dogs increases, it is imperative that such claims are documented empirically. The overall aims of this study were to record the proportion of MAD owners who have a dog that alerts to multiple health conditions or to people other than the target person and to determine whether any sociodemographic variables were associated with dogs alerting to multiple conditions, multiple people, or both. MAD owners completed an online survey that contained a series of forced choice questions. Sixty-one participants reported a total of 33 different conditions to which dogs alerted. Eighty-four percent of participants reported that their dog alerted to multiple conditions and 54% reported that their dog alerted to multiple people. This is the first study to document that a large percentage of people report that their MAD alerts to multiple conditions and/or to multiple people. We present a discussion of how these alerting abilities could develop, but questions about the underlying mechanisms remain.

Review on Volatolomic Studies as a Frontier Approach in Animal Research

This paper presents a comprehensive review of the research studies in volatolomics performed on animals so far. At first, the procedures proposed for the collection, preconcentration, and storing of the volatile organic compounds emitted by various biological samples of different animals are presented and discussed. Next, the results obtained in the analysis of the collected volatile samples with analytical equipment are shown. The possible volatile biomarkers identified for various diseases are highlighted for different types of diseases, animal species, and biological samples analyzed. The chemical classes of these compounds, as well as the biomarkers found in a higher number of animal diseases, are indicated, and their possible origin is analyzed. The studies that dealt with the diagnosis of various diseases from sample measurement with electronic nose systems are also presented and discussed. The paper ends with a final remark regarding the necessity of optimization and standardization of sample collection and analysis procedures for obtaining meaningful results.

COVID-19 detection by dogs: from physiology to field application-a review article

For years, the dog, man's best friend, was the most widely employed scent-detector tool for civilian and military purposes. Recently, many studies highlighted the role of canine olfactory ability in the medical field, specifically in detecting different infectious, metabolic and neoplastic conditions. The objective of this literature review is to clarify the rationale behind dog's ability to detect diseases, to assess the possible application for COVID-19 detection and to discuss the evidence available on the matter. Available evidence shows that properly trained disease-detector dogs are an efficient tool for identification of specific disease-associated volatile organic compounds marker profiles for a particular disease. And since COVID-19 positive persons have a specific volatilome different from non-infected persons, they can be recognised by the dogs, by sniffing different body fluids consequently aiding in the diagnosis of COVID-19. Possible applications of dogs as COVID-19 detectors will be an easy real-time mobile diagnostic aid with low cost and good performance. More evidence is needed to be able to describe standardised measures concerning the best fluid to test, testing procedure, time of possible detection according to disease evolution, risks associated with the dog exposure and to translate the good results in study setting into the real-life operational one.

Behavioral Immunity and Social Distancing in the Wild: The Same as in Humans?

The COVID-19 pandemic imposed new norms on human interactions, perhaps best reflected in the widespread application of social distancing. But social distancing is not a human invention and has evolved independently in species as dissimilar as apes and lobsters. Epidemics are common in the wild, where their spread is enhanced by animal movement and sociality while curtailed by population fragmentation, host behavior, and the immune systems of hosts. In the present article, we explore the phenomenon of behavioral immunity in wild animals as compared with humans and its relevance to the control of disease in nature. We start by explaining the evolutionary benefits and risks of sociality, look at how pathogens have shaped animal evolution, and provide examples of pandemics in wild animal populations. Then we review the known occurrences of social distancing in wild animals, the cues used to enforce it, and its efficacy in controlling the spread of diseases in nature.

Induced volatolomics of pathologies

Volatolomics allows us to elucidate cell metabolic processes in real time. In particular, a volatile organic compound (VOC) excreted from our bodies may be specific for a certain disease, such that measuring this VOC may afford a simple, fast, accessible and safe diagnostic approach. Yet, finding the optimal endogenous volatile marker specific to a pathology is non-trivial because of interlaboratory disparities in sample preparation and analysis, as well as high interindividual variability. These limit the sensitivity and specificity of volatolomics and its applications in biological and clinical fields but have motivated the development of induced volatolomics. This approach aims to overcome issues by measuring VOCs that result not from an endogenous metabolite but, rather, from the pathogen-specific or metabolic-specific enzymatic metabolism of an exogenous biological or chemical probe. In this Review, we introduce volatile-compound-based probes and discuss how they can be exploited to detect and discriminate pathogenic infections, to assess organ function and to diagnose and monitor cancers in real time. We focus on cases in which labelled probes have informed us about metabolic processes and consider the potential and drawbacks of the probes for clinical trials. Beyond diagnostics, VOC-based probes may also be effective tools to explore biological processes more generally.

Toward the use of medical scent detection dogs for COVID-19 screening

Current testing for the presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus), which causes the novel coronavirus 2019 (COVID-19) infection, is typically reliant upon collection of nasal swab samples from subjects. These tests (reverse transcription polymerase chain reaction [RT-PCR] and antigen) are intrusive, can take significant time to process, and can give deleterious false negative and false positive results. Alternative methods for COVID-19 testing and screening are being studied, including the use of trained scent detection dogs to detect volatile organic compounds (VOCs) associated with the COVID virus. In August 2020 and October 2020, the first author (T.D.) searched MEDLINE/PubMed, Cochrane Library, Google Scholar, and additional news articles using keyword phrases including “COVID scent dogs,” “COVID sniffer dogs,” and “COVID detection dog,” returning a total of 13 articles, nine of which were duplicates. Four remaining peer-reviewed studies dedicated to determining the feasibility and efficacy of detecting and screening individuals who may be infected by the COVID-19 virus with scent detection dogs were then examined. In this narrative review, the authors describe the methodologies and results of the remaining four studies, which demonstrated that the sensitivity, specificity, and overall success rates reported by the summarized scent detection studies are comparable to or better than the standard RT-PCR and antigen testing procedures, meaning that scent detection dogs can likely be effectively employed to nonintrusively screen and identify individuals infected with the COVID-19 virus in hospitals, senior care facilities, schools, universities, airports, and even large public gatherings for sporting events and concerts.